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New computer model predicts where Ebola might strike next



Predicting where Ebola might strike next could be made easier thanks to a new computer model. The model tracks how changes in the environment and in human society can affect the spread of the deadly virus. It is predicted that Ebola outbreaks could be up to 60 percent more likely by 2070 if the world remains on the path to a warmer climate and a cooling economy.

Ebola kills on average half of all people who become infected with the virus. In earlier outbreaks, the death rate has risen to 90 percent. The ability to predict where Ebola might cause chaos next could save thousands of lives by ensuring that people are better able to recognize, care for and take action to stop the spread of the virus.

"The future is inherently uncertain. But policymakers and policymakers want to understand the breadth of future opportunities, "says Kristie Ebi, professor of global health at the University of Washington, The Verge . "They need information about what could happen to be better prepared."

The model could eventually be used to find out where people need to be vaccinated before an outbreak has a chance to gain a foothold or to allow a government David Redding, lead author of today's Nature Communications explains The Verge that he should take action at the borders where ill travelers could spread the disease. The model could also be modified for other diseases. Redding hopes that the new model will make people think about all the factors that can lead to the spread of a disease like Ebola ̵

1; from societal changes to animal behavior to a changing environment. "It's something we need to do to understand and solve these complex issues," says Redding.

People can catch Ebola by getting in close contact with the blood or body fluids of an infected person or animal. Scientists suggest that a fruit bat may have broken loose in West Africa in 2014, killing 11,325 people. The effects of climate change could change where bats and humans live and bring them in closer contact. Poverty – as other studies have shown, can also increase in a warming world – can also lead to people turning to riskier food sources, including wildlife bearing Ebola. And in places where poverty could pose a greater risk to humans, there are often no hospitals and clinics that could prevent the spread of the disease.

While climate change is affecting ecosystems, scientists and physicians have feared that zoonoses might break out (those that can spread from animals to humans) could be harder to predict. Ticks and mosquitoes were already on the move thanks to the warmer temperatures, bringing with them diseases such as Lyme, Dengue and Zika. "Contactability and frequency are key factors in the spread of infectious diseases," wrote Konstans Wells, an ecologist at Swansea University, to The Verge in an e-mail.

To determine the outlook for Ebola in 2070, researchers who developed the new mathematical model considered various scenarios of how the world could work together to reduce inequality, slow down population growth, and reduce greenhouse gas emissions. They saw the likelihood of new outbreaks, unless people took action to combat each of these factors.

Her method shows how complicated it can be to find out all the problems that can trigger an epidemic. To understand the current risk of outbreaks, researchers used the model to analyze data on climate change, land use, population growth and poverty. Places where epidemics have already broken out, such as the Democratic Republic of the Congo and Gabon, have been identified. She also pointed to places, especially in Nigeria, where there was no epidemic. This could be because the health infrastructure at these sites was better prepared for the risk.

Whether a community has a strong health system and opportunities to detect and track a disease can, according to Daniel Bausch, a member of the EU Executive Committee, make the distinction between an isolated case of Ebola and a widespread disaster. American Tropical Tropical Society. The model could also help to solve this problem. In places where there are not many resources available to track the onset of disease, predictive models such as this official and humanitarian organizations could help draw attention to an epidemic. He warns, however, that they must have confidence in the model.

"Do I expect this to be a Eureka affair, with which we can now predict all areas where Ebola will appear? I'm still skeptical, "says Bausch. "Only time will tell."


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